{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction: Testing Feature Selector\n",
    "\n",
    "In this notebook we will test the feature selector using two additional datasets. We will try out many of the `FeatureSelector` methods on these standard machine learning sets to make sure that it is a minimum working product.\n",
    "\n",
    "https://github.com/WillKoehrsen/feature-selector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from feature_selector import FeatureSelector\n",
    "\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Air Quality Dataset \n",
    "\n",
    "Regression machine learning task\n",
    "\n",
    "From UCI repository: https://archive.ics.uci.edu/ml/datasets/Air+Quality#"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Time</th>\n",
       "      <th>CO(GT)</th>\n",
       "      <th>PT08.S1(CO)</th>\n",
       "      <th>NMHC(GT)</th>\n",
       "      <th>C6H6(GT)</th>\n",
       "      <th>PT08.S2(NMHC)</th>\n",
       "      <th>NOx(GT)</th>\n",
       "      <th>PT08.S3(NOx)</th>\n",
       "      <th>NO2(GT)</th>\n",
       "      <th>PT08.S4(NO2)</th>\n",
       "      <th>PT08.S5(O3)</th>\n",
       "      <th>T</th>\n",
       "      <th>RH</th>\n",
       "      <th>AH</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>23587200.0</td>\n",
       "      <td>18</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>1360</td>\n",
       "      <td>150</td>\n",
       "      <td>11</td>\n",
       "      <td>9</td>\n",
       "      <td>1046</td>\n",
       "      <td>166</td>\n",
       "      <td>1056</td>\n",
       "      <td>113</td>\n",
       "      <td>1692</td>\n",
       "      <td>1268</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>23587200.0</td>\n",
       "      <td>19</td>\n",
       "      <td>2</td>\n",
       "      <td>1292</td>\n",
       "      <td>112</td>\n",
       "      <td>9</td>\n",
       "      <td>4</td>\n",
       "      <td>955</td>\n",
       "      <td>103</td>\n",
       "      <td>1174</td>\n",
       "      <td>92</td>\n",
       "      <td>1559</td>\n",
       "      <td>972</td>\n",
       "      <td>13</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>23587200.0</td>\n",
       "      <td>20</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1402</td>\n",
       "      <td>88</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>939</td>\n",
       "      <td>131</td>\n",
       "      <td>1140</td>\n",
       "      <td>114</td>\n",
       "      <td>1555</td>\n",
       "      <td>1074</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23587200.0</td>\n",
       "      <td>21</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1376</td>\n",
       "      <td>80</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>948</td>\n",
       "      <td>172</td>\n",
       "      <td>1092</td>\n",
       "      <td>122</td>\n",
       "      <td>1584</td>\n",
       "      <td>1203</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>23587200.0</td>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>1272</td>\n",
       "      <td>51</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>836</td>\n",
       "      <td>131</td>\n",
       "      <td>1205</td>\n",
       "      <td>116</td>\n",
       "      <td>1490</td>\n",
       "      <td>1110</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date  Time  CO(GT)  PT08.S1(CO)  NMHC(GT)  C6H6(GT)  PT08.S2(NMHC)  \\\n",
       "0  23587200.0    18       2            6      1360       150             11   \n",
       "1  23587200.0    19       2         1292       112         9              4   \n",
       "2  23587200.0    20       2            2      1402        88              9   \n",
       "3  23587200.0    21       2            2      1376        80              9   \n",
       "4  23587200.0    22       1            6      1272        51              6   \n",
       "\n",
       "   NOx(GT)  PT08.S3(NOx)  NO2(GT)  PT08.S4(NO2)  PT08.S5(O3)     T    RH  AH  \n",
       "0        9          1046      166          1056          113  1692  1268  13  \n",
       "1      955           103     1174            92         1559   972    13   3  \n",
       "2        0           939      131          1140          114  1555  1074  11  \n",
       "3        2           948      172          1092          122  1584  1203  11  \n",
       "4        5           836      131          1205          116  1490  1110  11  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "air_quality = pd.read_csv('data/AirQualityUCI.csv')\n",
    "air_quality['Date'] = pd.to_datetime(air_quality['Date'])\n",
    "air_quality['Date'] = (air_quality['Date'] - air_quality['Date'].min()).dt.total_seconds()\n",
    "air_quality['Time'] = [int(x[:2]) for x in air_quality['Time']]\n",
    "air_quality.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "labels = air_quality['PT08.S5(O3)']\n",
    "air_quality = air_quality.drop(columns = 'PT08.S5(O3)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "fs = FeatureSelector(data = air_quality, labels = labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 features with greater than 0.50 missing values.\n",
      "\n",
      "0 features with a single unique value.\n",
      "\n",
      "8 features with a correlation greater than 0.70.\n",
      "\n",
      "Training Gradient Boosting Model\n",
      "\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "Did not meet early stopping. Best iteration is:\n",
      "[969]\tvalid_0's l2: 1073.52\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "Did not meet early stopping. Best iteration is:\n",
      "[987]\tvalid_0's l2: 961.098\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "Did not meet early stopping. Best iteration is:\n",
      "[998]\tvalid_0's l2: 2179.76\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "Did not meet early stopping. Best iteration is:\n",
      "[991]\tvalid_0's l2: 1073.42\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "Did not meet early stopping. Best iteration is:\n",
      "[1000]\tvalid_0's l2: 884.694\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "Did not meet early stopping. Best iteration is:\n",
      "[994]\tvalid_0's l2: 1059.25\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "Did not meet early stopping. Best iteration is:\n",
      "[1000]\tvalid_0's l2: 901.661\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "Did not meet early stopping. Best iteration is:\n",
      "[1000]\tvalid_0's l2: 963.885\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "Did not meet early stopping. Best iteration is:\n",
      "[981]\tvalid_0's l2: 943.787\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "Did not meet early stopping. Best iteration is:\n",
      "[1000]\tvalid_0's l2: 925.407\n",
      "\n",
      "0 features with zero importance after one-hot encoding.\n",
      "\n",
      "9 features required for cumulative importance of 0.90 after one hot encoding.\n",
      "5 features that do not contribute to cumulative importance of 0.90.\n",
      "\n",
      "11 total features out of 14 identified for removal after one-hot encoding.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "fs.identify_all(selection_params = {'missing_threshold': 0.5, 'correlation_threshold': 0.7, \n",
    "                                    'task': 'regression', 'eval_metric': 'l2', \n",
    "                                     'cumulative_importance': 0.9})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f0958eff98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fs.plot_collinear()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f095b94898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fs.plot_missing()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f095c34198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f095c34e48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10 features required for 0.90 of cumulative importance\n"
     ]
    }
   ],
   "source": [
    "fs.plot_feature_importances(threshold = 0.9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Time</th>\n",
       "      <th>CO(GT)</th>\n",
       "      <th>PT08.S1(CO)</th>\n",
       "      <th>NMHC(GT)</th>\n",
       "      <th>C6H6(GT)</th>\n",
       "      <th>PT08.S2(NMHC)</th>\n",
       "      <th>NOx(GT)</th>\n",
       "      <th>PT08.S3(NOx)</th>\n",
       "      <th>NO2(GT)</th>\n",
       "      <th>PT08.S4(NO2)</th>\n",
       "      <th>T</th>\n",
       "      <th>RH</th>\n",
       "      <th>AH</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>23587200.0</td>\n",
       "      <td>18</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>1360</td>\n",
       "      <td>150</td>\n",
       "      <td>11</td>\n",
       "      <td>9</td>\n",
       "      <td>1046</td>\n",
       "      <td>166</td>\n",
       "      <td>1056</td>\n",
       "      <td>1692</td>\n",
       "      <td>1268</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>23587200.0</td>\n",
       "      <td>19</td>\n",
       "      <td>2</td>\n",
       "      <td>1292</td>\n",
       "      <td>112</td>\n",
       "      <td>9</td>\n",
       "      <td>4</td>\n",
       "      <td>955</td>\n",
       "      <td>103</td>\n",
       "      <td>1174</td>\n",
       "      <td>92</td>\n",
       "      <td>972</td>\n",
       "      <td>13</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>23587200.0</td>\n",
       "      <td>20</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1402</td>\n",
       "      <td>88</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>939</td>\n",
       "      <td>131</td>\n",
       "      <td>1140</td>\n",
       "      <td>1555</td>\n",
       "      <td>1074</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23587200.0</td>\n",
       "      <td>21</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1376</td>\n",
       "      <td>80</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>948</td>\n",
       "      <td>172</td>\n",
       "      <td>1092</td>\n",
       "      <td>1584</td>\n",
       "      <td>1203</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>23587200.0</td>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>1272</td>\n",
       "      <td>51</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>836</td>\n",
       "      <td>131</td>\n",
       "      <td>1205</td>\n",
       "      <td>1490</td>\n",
       "      <td>1110</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date  Time  CO(GT)  PT08.S1(CO)  NMHC(GT)  C6H6(GT)  PT08.S2(NMHC)  \\\n",
       "0  23587200.0    18       2            6      1360       150             11   \n",
       "1  23587200.0    19       2         1292       112         9              4   \n",
       "2  23587200.0    20       2            2      1402        88              9   \n",
       "3  23587200.0    21       2            2      1376        80              9   \n",
       "4  23587200.0    22       1            6      1272        51              6   \n",
       "\n",
       "   NOx(GT)  PT08.S3(NOx)  NO2(GT)  PT08.S4(NO2)     T    RH  AH  \n",
       "0        9          1046      166          1056  1692  1268  13  \n",
       "1      955           103     1174            92   972    13   3  \n",
       "2        0           939      131          1140  1555  1074  11  \n",
       "3        2           948      172          1092  1584  1203  11  \n",
       "4        5           836      131          1205  1490  1110  11  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fs.data_all.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['missing', 'single_unique', 'collinear', 'zero_importance', 'low_importance'] methods have been run\n",
      "\n",
      "Removed 11 features\n"
     ]
    }
   ],
   "source": [
    "air_quality_removed = fs.remove(methods = 'all', keep_one_hot=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'collinear': ['PT08.S1(CO)',\n",
       "  'NMHC(GT)',\n",
       "  'NOx(GT)',\n",
       "  'PT08.S3(NOx)',\n",
       "  'PT08.S4(NO2)',\n",
       "  'T',\n",
       "  'RH',\n",
       "  'AH'],\n",
       " 'low_importance': ['PT08.S4(NO2)',\n",
       "  'PT08.S2(NMHC)',\n",
       "  'NMHC(GT)',\n",
       "  'C6H6(GT)',\n",
       "  'CO(GT)'],\n",
       " 'missing': [],\n",
       " 'single_unique': [],\n",
       " 'zero_importance': []}"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fs.removal_ops"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Insurance Dataset\n",
    "\n",
    "Classification machine learning problem.\n",
    "\n",
    "Formatted data from Kaggle: https://www.kaggle.com/uciml/caravan-insurance-challenge/data\n",
    "Originally from UCI machine learning repository: https://archive.ics.uci.edu/ml/datasets/Insurance+Company+Benchmark+%28COIL+2000%29"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MOSTYPE</th>\n",
       "      <th>MAANTHUI</th>\n",
       "      <th>MGEMOMV</th>\n",
       "      <th>MGEMLEEF</th>\n",
       "      <th>MOSHOOFD</th>\n",
       "      <th>MGODRK</th>\n",
       "      <th>MGODPR</th>\n",
       "      <th>MGODOV</th>\n",
       "      <th>MGODGE</th>\n",
       "      <th>MRELGE</th>\n",
       "      <th>...</th>\n",
       "      <th>ALEVEN</th>\n",
       "      <th>APERSONG</th>\n",
       "      <th>AGEZONG</th>\n",
       "      <th>AWAOREG</th>\n",
       "      <th>ABRAND</th>\n",
       "      <th>AZEILPL</th>\n",
       "      <th>APLEZIER</th>\n",
       "      <th>AFIETS</th>\n",
       "      <th>AINBOED</th>\n",
       "      <th>ABYSTAND</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>40</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 85 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   MOSTYPE  MAANTHUI  MGEMOMV  MGEMLEEF  MOSHOOFD  MGODRK  MGODPR  MGODOV  \\\n",
       "0       33         1        3         2         8       0       5       1   \n",
       "1       37         1        2         2         8       1       4       1   \n",
       "2       37         1        2         2         8       0       4       2   \n",
       "3        9         1        3         3         3       2       3       2   \n",
       "4       40         1        4         2        10       1       4       1   \n",
       "\n",
       "   MGODGE  MRELGE    ...     ALEVEN  APERSONG  AGEZONG  AWAOREG  ABRAND  \\\n",
       "0       3       7    ...          0         0        0        0       1   \n",
       "1       4       6    ...          0         0        0        0       1   \n",
       "2       4       3    ...          0         0        0        0       1   \n",
       "3       4       5    ...          0         0        0        0       1   \n",
       "4       4       7    ...          0         0        0        0       1   \n",
       "\n",
       "   AZEILPL  APLEZIER  AFIETS  AINBOED  ABYSTAND  \n",
       "0        0         0       0        0         0  \n",
       "1        0         0       0        0         0  \n",
       "2        0         0       0        0         0  \n",
       "3        0         0       0        0         0  \n",
       "4        0         0       0        0         0  \n",
       "\n",
       "[5 rows x 85 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "insurance = pd.read_csv('data/caravan-insurance-challenge.csv')\n",
    "insurance = insurance[insurance['ORIGIN'] == 'train']\n",
    "labels = insurance['CARAVAN']\n",
    "insurance = insurance.drop(columns = ['ORIGIN', 'CARAVAN'])\n",
    "insurance.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "fs = FeatureSelector(data = insurance, labels = labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 features with greater than 0.80 missing values.\n",
      "\n",
      "0 features with a single unique value.\n",
      "\n",
      "25 features with a correlation greater than 0.85.\n",
      "\n",
      "Training Gradient Boosting Model\n",
      "\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "Early stopping, best iteration is:\n",
      "[104]\tvalid_0's auc: 0.754092\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "Early stopping, best iteration is:\n",
      "[3]\tvalid_0's auc: 0.752314\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "Early stopping, best iteration is:\n",
      "[33]\tvalid_0's auc: 0.750626\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "Early stopping, best iteration is:\n",
      "[90]\tvalid_0's auc: 0.806804\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "Early stopping, best iteration is:\n",
      "[53]\tvalid_0's auc: 0.767512\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "Early stopping, best iteration is:\n",
      "[85]\tvalid_0's auc: 0.798246\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "Early stopping, best iteration is:\n",
      "[115]\tvalid_0's auc: 0.788672\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "Early stopping, best iteration is:\n",
      "[127]\tvalid_0's auc: 0.83582\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "Early stopping, best iteration is:\n",
      "[71]\tvalid_0's auc: 0.784331\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "Early stopping, best iteration is:\n",
      "[149]\tvalid_0's auc: 0.735016\n",
      "\n",
      "18 features with zero importance after one-hot encoding.\n",
      "\n",
      "31 features required for cumulative importance of 0.80 after one hot encoding.\n",
      "54 features that do not contribute to cumulative importance of 0.80.\n",
      "\n",
      "54 total features out of 85 identified for removal after one-hot encoding.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "fs.identify_all(selection_params = {'missing_threshold': 0.8, 'correlation_threshold': 0.85, \n",
    "                                    'task': 'classification', 'eval_metric': 'auc', \n",
    "                                     'cumulative_importance': 0.8})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f096d65390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f0959dcb38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "32 features required for 0.80 of cumulative importance\n"
     ]
    }
   ],
   "source": [
    "fs.plot_feature_importances(threshold=0.8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f092004588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fs.plot_collinear()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Removed 18 features\n"
     ]
    }
   ],
   "source": [
    "insurance_missing_zero = fs.remove(methods = ['missing', 'zero_importance'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['missing', 'single_unique', 'collinear', 'zero_importance', 'low_importance'] methods have been run\n",
      "\n",
      "Removed 54 features\n"
     ]
    }
   ],
   "source": [
    "insurance_removed = fs.remove(methods = 'all', keep_one_hot=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>feature</th>\n",
       "      <th>importance</th>\n",
       "      <th>normalized_importance</th>\n",
       "      <th>cumulative_importance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>PBRAND</td>\n",
       "      <td>175.2</td>\n",
       "      <td>0.070361</td>\n",
       "      <td>0.070361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MOSTYPE</td>\n",
       "      <td>167.9</td>\n",
       "      <td>0.067430</td>\n",
       "      <td>0.137791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>PPERSAUT</td>\n",
       "      <td>106.5</td>\n",
       "      <td>0.042771</td>\n",
       "      <td>0.180562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MINKM30</td>\n",
       "      <td>96.6</td>\n",
       "      <td>0.038795</td>\n",
       "      <td>0.219357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>MBERMIDD</td>\n",
       "      <td>81.5</td>\n",
       "      <td>0.032731</td>\n",
       "      <td>0.252088</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    feature  importance  normalized_importance  cumulative_importance\n",
       "0    PBRAND       175.2               0.070361               0.070361\n",
       "1   MOSTYPE       167.9               0.067430               0.137791\n",
       "2  PPERSAUT       106.5               0.042771               0.180562\n",
       "3   MINKM30        96.6               0.038795               0.219357\n",
       "4  MBERMIDD        81.5               0.032731               0.252088"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fs.feature_importances.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Conclusions\n",
    "\n",
    "More testing is needed and the `FeatureSelector` can currently not handle datetimes. Nonetheless, this is a good start with decent results!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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